Prevalence, diagnostic modalities, amputation rate, and overall mortality of arterial injuries associated with lower limb fractures/dislocations: A systematic review and meta-analysis
Notice bibliographique
Résumé
Background: Data on the prevalence, diagnostic modalities, management sequence, and mortality associated with lower limb fractures/dislocations vary significantly between studies and often do not account for the impact of arterial injury associated with fractures/dislocations on the risks of ischemia, amputation, and severe disability-posing major therapeutic challenges.Considering these uncertain things, we aimed to determine the prevalence, diagnostic modalities, amputation rate, and overall mortality associated with these injuries. Methods:We conducted a systematic review and meta-analysis following the Meta-Analyses Of Observational Studies in Epidemiology (MOOSE) guidelines.A comprehensive literature was performed in Medline, Embase, and the World Health Organization Global Health Library, covering the period from January 1, 1960, to April 2024, with no language restrictions.We included observational studies (cohort studies, cross-sectional studies, case-control studies, and retrospective series) reporting on the prevalence, secondary amputation rate, diagnostic and therapeutic modality techniques, histopathological type of vascular injuries, management sequence, and time to hospital admission in cases of combined vascular and musculoskeletal injuries.Two reviewers independently selected studies and extracted data, and methodological quality was assessed using the Newcastle-Ottawa Scale.Pooled estimates for prevalence, amputation, and mortality rates were calculated using meta-analysis.Heterogeneity was assessed using Cochran's Q 2 test and quantified by the I 2 statistic.All analyses were performed using R software version 4.4.2 for Windows. Results:The global prevalence of vascular injuries associated with musculoskeletal trauma was 37% (95% confidence interval [CI], 25%-49%), with substantial heterogeneity across studies (I 2 = 100%; P < .00001).The most frequently reported vascular injury was arterial transection (complete or partial), found in 278 cases (46.3%).Regarding treatment, open surgery was predominant, with vascular bypass in 56.71% of the lower limb trauma population, far ahead of other techniques.Arteriography was historically the most frequently used diagnostic modality, whereas computed tomography angiography has become the most common since the 1990s.The overall amputation rate was 14% (95% CI, 11%-17%; I 2 = 97%; P < .00001),and the overall mortality rate was 9% (95% CI, 6%-12%; I 2 = 86%; P < .00001).Tibial fractures (proximal, midshaft, distal, and multifocal) were significantly associated with injuries to the anterior tibial artery (odds ratio [OR], 9.23; P < .001)and the posterior tibial artery (OR, 7.86; P = .005).Similarly, fibula fractures were associated with posterior tibial artery injury (OR, 7.80; P = .004).No significant association was found between pelvic fractures/hip dislocation and vascular injuries (P > .05).Finally, the amputation rate was significantly higher in patients who underwent initial vascular repair (19.5%) compared with those who first had fracture/dislocation reduction (6.5%; P < .001),whereas mortality rates did not significantly differ between the two treatment sequences (4% vs 3.85%; P > .05).Conclusions: Our analysis highlights a high prevalence and non-negligible rates of amputation and mortality in vascular injuries associated with musculoskeletal trauma, with a predominance of arterial transections.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».